Market Insight: Nine Ways AI Will Drive Decarbonization
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Executive Summary
Net zero and sustainability executives face multiple obstacles when implementing a decarbonization strategy, from creating a large repository of carbon data sourced across the organization to facing uncertainties around their net zero targets. As software vendors and consultancies incorporate AI into their products and offerings to provide solutions to common decarbonization challenges, they should carefully consider their positioning in the market, as well as unexplored opportunities for the application of AI to decarbonization use cases. Potential – and existing – applications span carbon data anomalies detection, carbon calculations facilitation, emissions forecasting, supply chain emissions hotspot identification, and methane leaks detection and prevention.
Table of contents
Applications of artificial intelligence will have a large net impact on decarbonizationAI lends itself to large emissions data sets and forward-looking analysis
Applying AI to decarbonization strategy development and implementation
Table of figures
Figure 1. AI helps overcome challenges to manage carbon data and implement decarbonization plansFigure 2. Net zero target-setting, pathways and forecasting is a high priority for over half of respondents
Organisations mentioned
Amazon Web Services (AWS), Avarni, Benchmark Gensuite, BNP Paribas, BrainBox AI, C3 AI, CO2 AI, Dynamon, ENGIE, Environmental Defense Fund, GE Vernova, GLYNT.AI, Google, IBM, Jua, Kayrros, Makersite, Microsoft, OpenAI, Persefoni, Sweep, Unravel CarbonAbout the authors
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